Gpu_Utilization_Monitoring

Name: Gpu_Utilization_Monitoring
Author: davidcastagnetoa

Checked

davidcastagnetoa·vlatest·devops

Monitors GPU utilization across your infrastructure, providing real-time insights to optimize performance and resource allocation.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

Run this in your project

terminal

$ npx skills add davidcastagnetoa/skills --skill gpu_utilization_monitoring -a claude-code

Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

davidcastagnetoa

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned 29 Sept 2026

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

Declares what it does: passed
SKILL.md parses and declares a name and a description.
SKILL.md exists, its frontmatter parses, and it declares a name and a description.
No undeclared network calls: passed
Makes no network calls.
Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.
No obfuscated payloads: passed
No encoded or obfuscated payloads.
No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.
No credential access: passed
Reads no keys, tokens, keychains or credential files.
Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.
No pipe-to-shell installers: passed
No pipe-to-shell or download-and-run installers.
No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.
Pinned to a commit: passed
Scanned davidcastagnetoa/skills at bd906f22af.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit: bd906f22af
Manifest: skills/gpu_utilization_monitoring/SKILL.md
Scanned: 1 file, 74 lines

This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.

What each check looks for →

About this skill

What it does

This skill monitors GPU utilization across a system. It provides real-time data on GPU usage, memory consumption, and temperature. This allows for proactive identification of bottlenecks or potential hardware issues impacting AI workloads.

When to use it

Troubleshooting slow training: Identify if GPUs are fully utilized during model training runs.
Capacity planning: Determine if existing GPU resources are sufficient for future workload demands.
Performance optimization: Pinpoint specific processes or models causing high GPU load.
Resource allocation: Dynamically adjust resource assignments based on observed GPU utilization patterns.

Key capabilities

Real-time GPU monitoring
GPU memory usage tracking
Temperature reporting

Example prompts

"Show me the current GPU utilization."
"What is the temperature of my GPUs?"
"Report GPU memory consumption for the last 5 minutes."

Tips & gotchas

This skill requires access to system monitoring tools and appropriate permissions to collect GPU data. Ensure the agent has the necessary privileges to accurately report on GPU status.